Distributed Systems

- ZAB Protocol.md

1. What Is Raft - A distributed consensus algorithm invented by Diego Ongaro. 2. Why Raft Is Needed - To solve the complexity of implementing Paxos. 3. Raft Algorithm Process 3.1. Roles - Leader - Follower - Candidate 3.2. Three Phases 3.2.1. Phase 1: Leader Election

1. What Is Gossip - An algorithm proposed by Xerox for replicating data among multiple nodes in a distributed database. - Nodes continuously exchange information, and after a period of time all nodes in the cluster will know the complete information. 2. Why Gossip Is Needed 3. Gossip Algorithm Process - Each node periodically and randomly selects a connected node to spread messages.

1. What Are Distributed Consistency Models - Different consistency models solve consistency problems to different degrees. 2. Categories of Distributed Consistency Models 2.1. Strong Consistency - C in CAP.md - Also called linearizability. 2.2. Weak Consistency - Eventual consistency - Causal consistency - Read-your-writes consistency - Session consistency - Monotonic-read consistency - Monotonic-write consistency - Prefix-read consistency

1. What Is Replication - The same data is stored on multiple machines. - Each node that stores the data is called a replica. 2. Why Replication Is Needed - Improve availability through data redundancy. - Improve read throughput through read/write separation. 3. Replication Architecture. 4. Replication Methods. 5. Replication Log Formats.

1. What Is Leader-Leader - There are multiple Leaders, and each Leader has multiple Followers. 2. Leader-Leader Use Cases - Multiple data centers. - Applications still need to continue working after the network is disconnected. 3. How Leader-Leader Works 3.1. Leader Election 3.2. Leaders Synchronize Data to Leaders.

1. What Is Leaderless Replication - There is no Leader. When the client writes, it sends the write request to all replicas in parallel; when it reads, it similarly sends the read request to all replicas in parallel. 2. Leaderless Replication Use Cases. 3. How Leaderless Replication Works 3.1. Data Synchronization 3.1.1. Write-Conflict Problem.

1. What Is Leader-Follower - There is exactly one Leader among the replicas, and all others are Followers. 2. Leader-Follower Use Cases - A single data center. 3. Leader Election - Select one replica as the Leader and use the other replicas as Followers.

1. What They Are - Data changes between replicas are generally tracked through replication logs, with several formats. 2. Categories 2.1. Physical Logs - Which page was modified, what was the original value, and what is the updated value. 2.2. Logical Logs - Which record was modified, further divided into Statement and Row.

1. Synchronous Replication - The Leader succeeds only after synchronizing to all Followers. 1. The client requests the Leader. 2. The Leader writes local data. 3. The Leader synchronizes to Followers. 4. The Leader returns success to the client. 2. Asynchronous Replication - The Leader succeeds once it writes locally.